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Hyperscanning approaches to human neuroscience aim to uncover the neural mechanisms of social interaction. They have been largely guided by the expectation that increased levels of engagement between two persons will be supported by higher levels of inter-brain synchrony (IBS). A common approach to measuring IBS is phase synchrony in the context of EEG hyperscanning. Yet the growing number of experimental findings does not yield a straightforward interpretation, which has prompted critical reflections about the field’s theoretical and methodological principles. In this perspective piece, we make a conceptual contribution to this debate by considering the role of a possibly overlooked effect of inter-brain desynchronization (IBD), as for example measured by decreased phase synchrony. A principled reason to expect this role comes from the recent proposal of irruption theory, which operationalizes the efficacy of a person’s subjective involvement in behavior generation in terms of increased neural entropy. Accordingly, IBD is predicted to increase with one or more participant’s socially motivated subjective involvement in interaction, because of the associated increase in their neural entropy. Additionally, the relative prominence of IBD compared to IBS is expected to vary in time, as well as across frequency bands, depending on the extent that subjective involvement is elicited by the task and/or desired by the person. If irruption theory is on the right track, it could thereby help to explain the notable variability of IBS in social interaction in terms of a countertendency from another factor: IBD due to subjective involvement.

Introduction Parent–child synchrony, defined as the coordination of biological and behavioral processes during social interactions, serves as a critical predictor of children's psychological health and behavioral outcomes. Although recent research has examined its neurobiological underpinnings, the longitudinal relationship between mother–child synchrony and preadolescent behavioral problems in China remains underexplored. Methods This longitudinal study followed mother–child dyads at ages 7, 9, and 11, focusing on the trajectory of children's behavioral problems. At age 7, functional near‐infrared spectroscopy was employed during a mother–child drawing task to measure neural synchrony. Neural synchrony was assessed using wavelet transform coherence to capture both timealigned and time‐lagged dynamics during naturalistic mother–child interaction. Group‐level analyses linked these neural patterns to behavioral synchrony and developmental outcomes using regression models and exploratory structural equation modeling. Results Results revealed that time‐lagged neural synchrony, involving the mother's temporoparietal junction and the child's dorsolateral prefrontal cortex, was significantly associated with the predominant form of temporally sequential behavioral synchrony. Furthermore, mother‐led child‐following behavioral synchrony and 13‐s time‐lagged neural synchrony were linked to fewer externalizing problems in children. Conclusions Main findings reveal that specific patterns of time‐lagged mother–child neural synchrony, particularly when the mother leads and the child follows, are associated with reduced externalizing behavioral problems in children. These findings provide preliminary evidence regarding neurocognitive processes relevant to children's social‐emotional development from middle childhood to preadolescence. These findings are consistent with emerging literature indicating that delayed but structured interbrain dynamics may contribute to co‐regulated emotional development. However, the current evidence remains preliminary and warrants further validation using multimodal synchrony measures and larger longitudinal cohorts to establish causal pathways.

Neurons can transmit information about the characteristics of a stimulus through the spike rate of neurons and synchronization of the neurons. Various association measure can be used to describe how \"synchronous\" two spike trains are. We propose a new measure of synchrony, the conditional synchrony measure, which is the probability of firing together given that at least one of the two neurons is active. Focus is on the specification of a flexible marginal model for multivariate correlated binary data together with a pseudolikelihood estimation approach, to adequately and directly describe the measures of interest. A joint model must allow different time- and covariate-dependent firing rates for each neuron, and also must account for the association between them. The association between neurons might depend on covariates as well.

While substantial research supports the role of parent–child interactions on the emergence of psychiatric symptoms, few studies have explored biological mechanisms for this association. The current study explored behavioral and neural parent–child synchronization during frustration and play as predictors of internalizing and externalizing behaviors across a span of 1.5 years. Parent–child dyads first came to the laboratory when the child was 4–5 years old and completed the Disruptive Behavior Diagnostic Observation Schedule: Biological Synchrony (DB-DOS: BioSync) task while functional near-infrared spectroscopy (fNIRS) data were recorded. Parents reported on their child's internalizing and externalizing behaviors using the Child Behavior Checklist (CBCL) four times over 1.5 years. Latent growth curve (LGC) modeling was conducted to assess neural and behavioral synchrony as predictors of internalizing and externalizing trajectories. Consistent with previous investigations in this age range, on average, internalizing and externalizing behaviors decreased over the four time points. Parent–child neural synchrony during a period of play predicted rate of change in internalizing but not externalizing behaviors such that higher parent–child neural synchrony was associated with a more rapid decrease in internalizing behaviors. Our results suggest that a parent–child dyad's ability to coordinate neural activation during positive interactions might serve as a protective mechanism in the context of internalizing behaviors.

Dance has traditionally been viewed from a Eurocentric perspective as a mode of self-expression that involves the human body moving through space, performed for the purposes of art, and viewed by an audience. In this Hypothesis and Theory article, we synthesize findings from anthropology, sociology, psychology, dance pedagogy, and neuroscience to propose The Synchronicity Hypothesis of Dance, which states that humans dance to enhance both intra- and inter-brain synchrony. We outline a neurocentric definition of dance, which suggests that dance involves neurobehavioral processes in seven distinct areas including sensory, motor, cognitive, social, emotional, rhythmic, and creative. We explore The Synchronicity Hypothesis of Dance through several avenues. First, we examine evolutionary theories of dance, which suggest that dance drives interpersonal coordination. Second, we examine fundamental movement patterns, which emerge throughout development and are omnipresent across cultures of the world. Third, we examine how each of the seven neurobehaviors increases intra- and inter-brain synchrony. Fourth, we examine the neuroimaging literature on dance to identify the brain regions most involved in and affected by dance. The findings presented here support our hypothesis that we engage in dance for the purpose of intrinsic reward, which as a result of dance-induced increases in neural synchrony, leads to enhanced interpersonal coordination. This hypothesis suggests that dance may be helpful to repattern oscillatory activity, leading to clinical improvements in autism spectrum disorder and other disorders with oscillatory activity impairments. Finally, we offer suggestions for future directions and discuss the idea that our consciousness can be redefined not just as an individual process but as a shared experience that we can positively influence by dancing together.

Conversations are an essential form of communication in daily family life. Specific patterns of caregiver-child conversations have been linked to children's socio-cognitive development and child-relationship quality beyond the immediate family environment. Recently, interpersonal neural synchronization has been proposed as a neural mechanism supporting conversation. Here, we present a functional near-infrared spectroscopy (fNIRS) hyperscanning study looking at the temporal dynamics of neural synchrony during mother-child conversation. Preschoolers (20 boys and 20 girls, M age 5;07 years) and their mothers (M age 36.37 years) were tested simultaneously with fNIRS hyperscanning while engaging in a free verbal conversation lasting for 4 min. Neural synchrony (using wavelet transform coherence analysis) was assessed over time. Furthermore, each conversational turn was coded for conversation patterns comprising turn-taking, relevance, contingency and intrusiveness. Results from linear mixed-effects modeling revealed that turn-taking, but not relevance, contingency or intrusiveness predicted neural synchronization during the conversation over time. Results are discussed to point out possible variables affecting parent-child conversation quality and the potential functional role of interpersonal neural synchronization for parent-child conversation. (ZPID).

Abstract Hyperscanning—simultaneous brain scanning of two or more individuals—holds great promise in elucidating the neurobiological underpinnings of social cognitive functions. This article focuses on functional magnetic resonance imaging (fMRI) hyperscanning and identifies promising targets for studying the neuroscience of social interaction with fMRI hyperscanning. Specifically, we present applications of fMRI hyperscanning in the study of social interaction along with promising analysis approaches for fMRI hyperscanning, with its high spatial and low temporal resolution. We first review fMRI hyperscanning studies in social neuroscience and evaluate the premise of using this costly neuroimaging paradigm. Many second-person social neuroscience studies are possible without fMRI hyperscanning. However, certain fundamental aspects of social cognition in real-life social interactions, including different roles of interactors, shared intention emerging through interaction and history of interaction, can be addressed only with hyperscanning. We argue that these fundamental aspects have not often been investigated in fMRI hyperscanning studies. We then discuss the implication of the signal coupling found in fMRI hyperscanning and consider analysis approaches that make fair use of it. With fMRI hyperscanning, we can explore not only synchronous brain activations but whole-brain asymmetric activation patterns with a lagged association between interacting individuals.

Interpersonal synchronization involves the alignment of behavioral, affective, physiological, and brain states during social interactions. It facilitates empathy, emotion regulation, and prosocial commitment. Mental disorders characterized by social interaction dysfunction, such as Autism Spectrum Disorder (ASD), Reactive Attachment Disorder (RAD), and Social Anxiety Disorder (SAD), often exhibit atypical synchronization with others across multiple levels. With the introduction of the \"second-person\" neuroscience perspective, our understanding of interpersonal neural synchronization (INS) has improved, however, so far, it has hardly impacted the development of novel therapeutic interventions. To evaluate the potential of INS-based treatments for mental disorders, we performed two systematic literature searches identifying studies that directly target INS through neurofeedback (12 publications; 9 independent studies) or brain stimulation techniques (7 studies), following PRISMA guidelines. In addition, we narratively review indirect INS manipulations through behavioral, biofeedback, or hormonal interventions. We discuss the potential of such treatments for ASD, RAD, and SAD and using a systematic database search assess the acceptability of neurofeedback (4 studies) and neurostimulation (4 studies) in patients with social dysfunction. Although behavioral approaches, such as engaging in eye contact or cooperative actions, have been shown to be associated with increased INS, little is known about potential long-term consequences of such interventions. Few proof-of-concept studies have utilized brain stimulation techniques, like transcranial direct current stimulation or INS-based neurofeedback, showing feasibility and preliminary evidence that such interventions can boost behavioral synchrony and social connectedness. Yet, optimal brain stimulation protocols and neurofeedback parameters are still undefined. For ASD, RAD, or SAD, so far no randomized controlled trial has proven the efficacy of direct INS-based intervention techniques, although in general brain stimulation and neurofeedback methods seem to be well accepted in these patient groups. Significant work remains to translate INS-based manipulations into effective treatments for social interaction disorders. Future research should focus on mechanistic insights into INS, technological advancements, and rigorous design standards. Furthermore, it will be key to compare interventions directly targeting INS to those targeting other modalities of synchrony as well as to define optimal target dyads and target synchrony states in clinical interventions.

Interpersonal neural synchrony provides a neural index of how individuals align cognitively and socially during interaction. While previous work has shown that personality traits shape interpersonal behavior, and that trait similarity can enhance dyadic coordination, little is known about whether such similarity predicts neural synchrony. The present study used an electroencephalography (EEG) hyper-scanning methodology to investigate the relationship between the degree of similarity in Big 5 scores of interacting participants in dyads and their interbrain synchrony during naturalistic dialogue. A total of 23 female dyads completed the Big 5 questionnaire and performed a goal-oriented social task while each wearing lightweight EEG headsets. Similarity for each Big 5 personality scale was created by calculating the absolute difference between the two participants within each dyad. Interpersonal neural synchrony was measured using Dynamic Time Warping (DTW), which quantified the similarity between separate temporal signals, based on a time-frequency decomposition of EEG. Results showed that similarity of Conscientiousness scores within dyads significantly predicted interpersonal neural synchrony within dyads (with openness showing marginal prediction). No relationship was evident for any other Big 5 trait. These findings demonstrate that personality similarity, particularly in conscientiousness, contributes to interpersonal neural synchrony, highlighting a trait-based pathway through which social alignment emerges during naturalistic interaction.

Understanding the fundamental mechanisms governing fluctuating oscillations in large-scale cortical circuits is a crucial prelude to a proper knowledge of their role in both adaptive and pathological cortical processes. Neuroscience research in this area has much to gain from understanding the Kuramoto model, a mathematical model that speaks to the very nature of coupled oscillating processes, and which has elucidated the core mechanisms of a range of biological and physical phenomena. In this paper, we provide a brief introduction to the Kuramoto model in its original, rather abstract, form and then focus on modifications that increase its neurobiological plausibility by incorporating topological properties of local cortical connectivity. The extended model elicits elaborate spatial patterns of synchronous oscillations that exhibit persistent dynamical instabilities reminiscent of cortical activity. We review how the Kuramoto model may be recast from an ordinary differential equation to a population level description using the nonlinear Fokker-Planck equation. We argue that such formulations are able to provide a mechanistic and unifying explanation of oscillatory phenomena in the human cortex, such as fluctuating beta oscillations, and their relationship to basic computational processes including multistability, criticality, and information capacity.